Feature point identification method of mechanocardiography

ABSTRACT

A method to identify feature points associated with the heart valve movement, heart contraction or cardiac hemodynamics is revealed. The mechanocardiography (MCG) is a technology that makes use of vibrational waveforms acquired using at least one gravity sensor attached on one of the four heart valve auscultation sites on the body surface. The data of the electrocardiography (ECG) is recorded simultaneously with the MCG The feature points are identified by comparing P, R and T points of synchronized ECG with the MCG spectrum. By the time sequences and amplitudes of the feature points, the method provides additional clinical information of cardiac cycle abnormalities for diagnosis.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional application of U.S. patent applicationSer. No. 15/716,776, filed on 27 Sep. 2017, which is a divisionalapplication of U.S. patent application Ser. No. 14/993,228, filed on 12Jan. 2016 and now issued as U.S. Pat. No. 9,833,172, which is based onTaiwan Patent Application Serial No. 104105227, filed on 16 Feb. 2015,all of which are incorporated by reference.

FIELD OF THE INVENTION

The present invention relates to a method of measuring cardiacvibrations on the body surface, especially to identify feature pointsassociated with the mechanocardiography (MCG).

BACKGROUND OF THE INVENTION

Since cardiovascular diseases have accounted for top three of ten causesof death in Taiwan, public awareness on prevention of cardiovasculardiseases is increasing. The people with the cardiovascular diseasesinclude older age, hypertension, diabetes, hyperlipidemia, exposure totobacco, obesity, and a family history of cardiovascular diseases, etc.The doctor diagnose patients by understanding the detail of patientdisease history and checking with the equipment such aselectrocardiogram (ECG), stress ECG phonocardiogram, echocardiography,nuclear medical imaging study, cardiac computerized tomography (CT)scan, cardiac magnetic resonance imaging (MRI), etc. There are two majorproblems of heart valves: valvular stenosis, which is inadequateopening, and valvular regurgitation, which is backward leakage of bloodthrough closed valves. These problems result in elevated pressure orincreased volume in heart chambers, leading to deterioration of heartfunction.

Heart valvular system consists of mitral, tricuspid, aortic andpulmonary valves. Heart valves allow blood to circulate through themwhen they are open and prevent backward blood flow when they are closed.The mechanisms make unidirectional blood flow possible and preserveenergy. Each valve can develop stenotic and regurgitant disorders, andsome patients have valvular prolapse of mitral and tricuspide valves,which indicate elongated valves with leaflets prolapsed to the atrialchambers. The circulation of blood in cardiovascular dystem is asfollowing: deoxygenated blood returns to the right atrium fromperipheral venous system via the superior and inferior venae cavae (SVCand IVC). The right ventricle relaxes to allow blood to go into theright ventricle via the tricuspid valve and then contracts to pump bloodin the pulmonary circulation via the pulmonary valve. After oxygen (O₂)and carbon dioxide (CO₂) exchange in the lungs, oxygenated blood returnsto the left atrium. The left ventricle relaxes to allow blood to go intothe left ventricle via the mitral valve and then contracts to pump bloodin the systemic circulation via the aortic valve. During ventricularsystole and diastole, forward flow is allowed and backward flow isprevented by functioning valvular opening and closing.

The most commonly available exam of cardiac diseases is ECG whichprovides indirect evidences of valvular diseases. For example, aorticstenosis results in ventricular pressure overload and left ventricularhypertrophy. Thus an increased QRS amplitude, ST segment/T-waveabnormalities can be observed in ECG. However, the same findings can befound in other diseases. The evaluation of cardiac systolic anddiastolic function requires further chest X-ray, echocardiography andnuclear medical tests. Cardiac murmurs generated by valve insufficiencycan be heard using a stethoscope. There are some limitations: aphysician being able to check a single auscultation site at a time andthe narrow range of human hearing (20 Hz to 20 kHz). Some abnormal heartsounds, such as the third and the fourth heart sounds (S3 and S4) arerelatively lower in frequency, which might be beyond the limits of humanhearing and are missed in cases. Therefore, phonocardiography is used torecord heart sound to check the opening and closing timing of heartvalves. There is a time delay between heart valves closing and signalcaptured on body surface, leading to confusion in clinical evaluation.Chest X-ray reveals calcification of the valves, but it provides limitedinformation of valvular heart diseases and is not a useful tool forcontinuous monitoring because of radiation. Echocardiography is a usefultool to evaluate cardiac contraction and valvular function. The commonlyused echocardiographic modalities include M-mode, 2-D, 3-D, Doppler andcontrast echocardiography images. Chamber sizes and valvular motion canbe evaluated using M-mode echocardiography, and normal and abnormalblood flow can be detected using Doppler and contrast echocardiography.However, echocardiography machine is bulky, and professional personnelare required, making the exam very inconvenient and not suitable forcontinuous monitoring.

The conventional ways for checking heart valve defect include ECGphonocardiogram, echocardiography, and nuclear medical tests. However,these techniques have their limitations while in use. Such as, the ECGcan be used to estimate intervals of heart valve operation, but can't beused to check opening and closure of heart valves effectively. Thephonocardiograms can be used for checking the opening and closing ofheart valves, yet are unable to detect changes in blood flow of theheart. The echocardiography can be used to check the lumen diameter, theheart valve movement, the direction of blood flow, the velocity andturbulence of the blood flow in cardiac vessels, but poses problems inlong term monitoring. Thus there is room for improvement and a need toprovide a novel method for mechanocardiography that overcomes theshortcomings of conventional ways for checking heart valves. The methodnot only records heart valve operation and blood flow features forlong-term monitoring but also improves convenience and accuracy inmeasurement.

SUMMARY

Therefore, one of the primary object s of the present invention is toprovide a feature point identification method for mechanocardiographythat implements mechanocardiography (MCG) and electrocardiography (ECG)simultaneously by measuring vibrations on body surface. The P-wave peakand the R-wave peak of the ECG correspond to the MCG to get twocorresponding points. Then a transmitral atrial contraction maximal flowfeature point (MFA) between the two corresponding points of the MCG isretrieved. Thus convenience and accuracy of clinical disease assessmentare improved.

It is another object of the present invention to provide a feature pointidentification method for mechanocardiography that retrieves a lateralwall contraction maximal velocity feature point (LCV), a transaorticmaximal flow feature point (AF), and a septal wall contraction maximalvelocity feature point (SCV) after an R-wave peak corresponding point ofthe MCG to improve convenience and accuracy of clinical diseaseassessment.

It is a further object of the present invention to provide a featurepoint identification method for mechanocardiography that compares theR-wave peak and the T-wave peak of the ECG with the MCG to get twocorresponding points. Then a transpulmonary maximal flow feature point(PF) and a lateral wall contraction maximal velocity feature point (LCV)between the two corresponding points are retrieved. Thus convenience andaccuracy of clinical disease assessment are both improved.

It is a further object of the present invention to provide a featurepoint identification method for mechanocardiography that retrieves atransaortic maximal flow feature point (AF), a transpulmonary maximalflow feature point (PF) and a septal wall contraction maximal velocityfeature point (SCV) after a lateral wall contraction maximal velocityfeature point (LCV) to improve convenience and accuracy of clinicaldisease assessment.

In order to achieve the above objects, the measurement device of thepresent invention includes at least one gravity sensor, anelectrocardiographic (ECG) sensing module, a processor, a storage unitand a transmission unit. The gravity sensor and the ECG sensing moduleare electrically coupled to the processor while the processor iselectrically coupled to the storage unit and the transmission unit. Thestorage unit is electrically coupled to the transmission unit.

At least one gravity sensor is placed on at least one of the heart valveauscultation sites correspondingly. The heart valve auscultation sitesare on the body surface and correspond to the heart valves. The heartvalve auscultation sites include an aortic area, a mitral area, apulmonary area and a tricuspid area. The ECG sensing module includesthree limb leads.

The processor is used to receive at least one MCG obtained by thegravity sensor and the ECG obtained by the ECG sensing module. Theprocessor also retrieves peaks or valleys of P-waves, QRS complexes, andT-waves in the ECG. Then the peaks or valleys of the ECG are comparedwith at least one MCG to get at least one corresponding point of the MCGNext a plurality of feature points of the MCG before or after thecorresponding point is retrieved. The feature points of the MCG includea transmitral atrial contraction maximal flow feature point (MFA), alateral wall contraction maximal velocity feature point (LCV), atransaortic maximal flow feature point (AF), a transpulmonary maximalflow feature point (PF), and a septal wall contraction maximal velocityfeature point (SCV).

The storage unit receives the feature points of the MCG and records theECG and the MCG from the processor. The storage unit also delivers theECG and the MCG to a connected receiving device. The receiving devicecan be a portable device, a computer, or a display.

A feature point identification method for mechanocardiography of thepresent invention includes the following steps. Arrange a gravity sensorat an aortic area on the body surface which corresponds to the heartvalves to get a first MCG (MCG 1) via the gravity sensor. Then disposean electrocardiography (ECG) sensing module on a limb lead attachmentregion on the body surface to get an ECG Next, retrieve a P-wave peakand an R-wave peak of the ECG and correspond both the P-wave peak andthe R-wave peak to the MCG1, respectively, to get a first correspondingpoint and a second corresponding point. Retrieve a peak with the maximumvalue between the first corresponding point and the second correspondingpoint. The peak with the maximum value is a transmitral atrialcontraction maximal flow feature point (MFA).

The aortic area is present from the left second intercostal space at theleft sternal border, over the sternum rightward, to the right second tothird intercostal space at the right sternal border.

The limb lead attachment region includes one right arm (RA), one leftarm (LA), and one left leg (LL).

A feature point identification method for mechanocardiography of thepresent invention includes the following steps. First, place a gravitysensor on an aortic area on the body surface that corresponds to theheart valves to get a first MCG reading (MCG 1) by the gravity sensor.Then arrange an electrocardiography (ECG) sensing module at a limb leadattachment region on the body surface to get an ECG. Next, retrieve anR-wave peak of the ECG and correspond the R-wave peak to the MCG1 to geta second corresponding point. Retrieve a valley with the minimum valueand a peak thereafter in turn within an interval of 0.06 second afterthe second corresponding point. The peak is a lateral wall contractionmaximal velocity feature point (LCV).

A feature point identification method for mechanocardiography of thepresent invention includes the following steps. In the beginning,arrange a gravity sensor at an aortic area on the body surface thatcorresponds to the heart valves to get a first MCG reading (MCG 1) bythe gravity sensor. Then place an electrocardiography (ECG) sensingmodule on a limb lead attachment region on body surface to get an ECGNext, retrieve an R-wave peak of the ECG and correlate the R-wave peakto the MCG1 to get a second corresponding point. Retrieve a peak withthe maximum value within an interval of 0.07-0.1 seconds after thesecond corresponding point O2. The peak with the maximum value is atransaortic maximal flow feature point (AF).

A feature point identification method for mechanocardiography of thepresent invention includes the following steps. First, place a gravitysensor on an aortic area on the body surface that corresponds to theheart valves to get a first MCG reading (MCG1) by the gravity sensor.Then arrange an electrocardiography (ECG) sensing module at a limb leadattachment region on body surface to get an ECG Next retrieve an R-wavepeak of the ECG and correspond the R-wave peak to the MCG1 to get asecond corresponding point. Retrieve a valley with the minimum value anda peak thereafter in turn within an interval of 0.06 second after thesecond corresponding point while the peak is a lateral wall contractionmaximal velocity feature point (LCV). Then again retrieve a peak afterthe feature point LCV; this peak is a transaortic maximal flow featurepoint (AF).

A feature point identification method for mechanocardiography of thepresent invention includes the following steps. First arrange a gravitysensor at an aortic area on the body surface that corresponds to theheart valves to get a first MCG reading (MCG1) by the gravity sensor.Then place an electrocardiography (ECG) sensing module on a limb leadattachment region on the body surface to get an ECG Next retrieve anR-wave peak and a T-wave peak of the ECG1 and correspond the R-wave peakand the T-wave peak to the MCG1 to get a second corresponding point anda third corresponding point. Again, retrieve a peak with the maximumvalue within an interval between 0.1 seconds after the secondcorresponding point and the third corresponding point. The peak with themaximum value is a transpulmonary maximal flow feature point (PF).

A feature point identification method for mechanocardiography of thepresent invention includes the following steps. At first, set a gravitysensor at an aortic area on the body surface that corresponds to theheart valves to get a first MCG reading (MCG1) by the gravity sensor.Dispose an electrocardiography (ECG) sensing module on a limb leadattachment region on the body surface to get an ECG Then retrieve anR-wave peak and a T-wave peak of the ECG1 and correspond the R-wave peakand the T-wave peak to the MCG1 to get a second corresponding point anda third corresponding point. Next, retrieve a valley with the minimumvalue and a peak thereafter in turn within an interval of 0.06 secondsafter the second corresponding point. The peak is a lateral wallcontraction maximal velocity feature point (LCV). Retrieve a peak withthe maximum value within an interval between the feature point LCV andthe third corresponding point. The peak with the maximum value is atranspulmonary maximal flow feature point (PF).

A feature point identification method for mechanocardiography of thepresent invention includes the following steps. First, arrange a gravitysensor at a mitral area on the body surface that corresponds to theheart valves to get a second MCG reading (MCG 2) by the gravity sensor.Then place an electrocardiography (ECG) sensing module on a limb leadattachment region on the body surface to get an ECG Next retrieve aR-wave peak and a T-wave peak of the ECG1 and correspond the R-wave peakand the T-wave peak to the MCG2 to get a fourth corresponding point anda fifth corresponding point. Retrieve a peak with the maximum value inan interval between 0.04 seconds after the fourth corresponding pointand the fifth corresponding point while the peak with the maximum valueis a lateral wall contraction maximal velocity feature point (LCV).

The mitral area is present from the right fifth intercostal space at theright sternal border to the posterior axillary line.

A feature point identification method for mechanocardiography of thepresent invention includes the following steps. First, mount a gravitysensor on a pulmonary area on the body surface that corresponds to theheart valves to get a third MCG reading (MCG3) by the gravity sensor.Then dispose an electrocardiography (ECG) sensing module on a limb leadattachment region on the body surface to get an ECG Next, retrieve anR-wave peak of the ECG1 and correspond the R-wave peak to the MCG3 toget a sixth corresponding point. Retrieve a peak with the maximum valuewithin an interval between 0.07-0.1 seconds after the sixthcorresponding point. The peak with the maximum value is a septal wallcontraction maximal velocity feature point (SCV).

The pulmonary area is around the second left intercostal space at theleft sternal border, up to the first left intercostal space, a lowerpart of the clavicle, and then down to the third left intercostal spaceat the left sternal border.

A feature point identification method for mechanocardiography of thepresent invention includes the following steps. First, arrange aplurality of gravity sensors on an aortic area and a pulmonary area onthe body surface that corresponds to the heart valves to get a first MCGreading (MCG1) and a third MCG reading (MCG3), respectively, by thegravity sensors. Then place an electrocardiography (ECG) sensing moduleon a limb lead attachment region on the body surface to get an ECG Next,retrieve an R-wave peak of the ECG and correspond the R-wave peak to theMCG1 to get a second corresponding point. Retrieve a valley with theminimum value and a peak thereafter in turn within an interval of 0.06seconds after the second corresponding point. The peak is a lateral wallcontraction maximal velocity feature point (LCV). Then correspond thefeature point LCV to the MCG3 to get a seventh corresponding point ofthe MCG3. At last, retrieve a peak after the seventh corresponding pointand this peak is a septal wall contraction maximal velocity featurepoint (SCV).

A feature point identification method for mechanocardiography of thepresent invention includes the following steps. First, place a gravitysensor on a tricuspid area on the body surface that corresponds to aheart valve to get a fourth MCG reading (MCG4) by the gravity sensor.Then arrange an electrocardiography (ECG) sensing module on a limb leadattachment region on the body surface to get an ECG Next, retrieve anR-wave peak and a T-wave peak of the ECG1 and correspond the R-wave peakand the T-wave peak to the MCG4 to get an eighth corresponding point anda ninth corresponding point. Retrieve a peak with the maximum valuebetween the eighth corresponding point and the ninth correspondingpoint. The peak with the maximum value is a lateral wall contractionmaximal velocity feature point (LCV).

The tricuspid area is extended rightward from the left fourth to fifthintercostal space at the right sternal border.

BRIEF DESCRIPTION OF THE DRAWINGS

The structure and the technical means adopted by the present inventionto achieve the above and other objects can best be understood byreferring to the following detailed description of the preferredembodiments and the accompanying drawings, wherein:

FIG. 1 is a schematic drawing showing the structure of a measurementdevice that embodies the present invention;

FIG. 2 is a circuit diagram of a measurement device that embodies thepresent invention;

FIG. 3 is a schematic drawing showing heart valve auscultation sites onbody surface which pertain to the present invention;

FIG. 4 is the first flow chart showing the steps as related to thepresent invention;

FIG. 5 is the first graph showing signal strength versus time of thefirst observations according to the present invention;

FIG. 6 is the first comparative figure showing signal strength versustime as observed according to the present invention;

FIG. 7 is the second flow chart showing steps of the second set ofobservations according to the present invention;

FIG. 8 is the second graph showing signal strength versus time of thesecond set of observations according to the present invention;

FIG. 9 is the second comparative figure showing signal strength versustime of the second set of observations according to the presentinvention;

FIG. 10 is the third flow chart showing steps of the third set ofobservations according to the present invention;

FIG. 11 is the third graph showing signal strength versus time of thethird set of observations according to the present invention;

FIG. 12 is the third comparative figure showing signal strength versustime of the third set of observations according to the presentinvention;

FIG. 13 is the fourth flow chart showing steps of the fourth set ofobservations according to the present invention;

FIG. 14 is the fourth graph showing signal strength versus time of thefourth set of observations according to the present invention;

FIG. 15 is the fifth flow chart showing steps of the fifth set ofobservations according to the present invention;

FIG. 16 is the fifth graph showing signal strength versus time of thefifth set of observations according to the present invention;

FIG. 17 is the fourth comparative figure showing signal strength versustime of the fifth set of observations according to the presentinvention;

FIG. 18 is the sixth flow chart showing steps of the sixth set ofobservations according to the present invention;

FIG. 19 is the sixth graph showing signal strength versus time of thesixth set of observations according to the present invention;

FIG. 20 is the seventh flow chart showing steps of the seventh set ofobservations according to the present invention;

FIG. 21 is the seventh graph showing signal strength versus time of theseventh set of observations according to the present invention;

FIG. 22 is the fifth comparative figure showing signal strength versustime of the seventh set of observations according to the presentinvention;

FIG. 23 is the eighth flow chart showing steps of the eighth set ofobservations according to the present invention;

FIG. 24 is the eighth graph showing signal strength versus time of theeighth set of observations according to the present invention;

FIG. 25 is the sixth comparative figure showing signal strength versustime of the eighth set of observations according to the presentinvention;

FIG. 26 is the ninth flow chart showing steps of the ninth set ofobservations according to the present invention;

FIG. 27 is the ninth graph showing signal strength versus time of theninth set of observations according to the present invention;

FIG. 28 is the tenth flow chart showing steps of the tenth set ofobservations according to the present invention;

FIG. 29 is the tenth graph showing signal strength versus time of thetenth set of observations according to the present invention;

FIG. 30 is the seventh comparative figure showing signal strength versustime of the tenth set of observations according to the presentinvention.

DETAILED DESCRIPTION

Please refer to the following implementations and related details inorder to learn about the features and functions of the presentinvention.

There is a variety of tests available now for checking heart valveproblems including ECG phonocardiogram, echocardiography, and nuclearmedical tests. ECG is used to estimate intervals of heart valveoperation, but is unable to check the opening and closing of heartvalves. Users can check the opening and closing of heart valves via aphonocardiogram, yet are unable to observe changes in the blood flow ofthe heart. An Echocardiography can be used to check the lumen diameter,the heart valve movement, the direction of the blood flow, the velocity,and the turbulence of the blood flow in the cardiac vessels, but posesproblems of convenience and accuracy in measurement. Thus the presentinvention provides a feature point identification method formechanocardiography that retrieves vibration signals on body surface asa consequence of cardiac motion by at least one gravity sensor to get anMCG A variety of peaks and valleys of the MCG are retrieved in turn bycomparing the P-wave peak, R-wave peak and T-wave peak of the ECG gottenfrom the ECG sensing module with the MCG to get feature points relatedto heart valves, the cardiac cycle, or the blood in the heart. Thepresent invention is a breakthrough method that records heart valveoperation or cardiac blood features via portable gravity sensors. Themethod can be used for long term monitoring with higher convenience andaccuracy in measurement.

Refer to FIG. 1 and FIG. 2, a schematic drawing showing the structureand a circuit block diagram of a measurement device of an embodimentaccording to the present invention, respectively. The hardware of thepresent invention comprises a measurement device 1 that includes severalgravity sensors 11-14, an electrocardiographic (ECG) sensing module 15,a processor 16, a storage unit 17 and a transmission unit 18. Thegravity sensors 11-14 and the ECG sensing module 15 are electricallycoupled to the processor 16 while the processor 16 is electricallyconnected to the storage unit 17 and the transmission unit 18. Thestorage unit 17 is electrically coupled to the transmission unit 18.

Refer to FIG. 3, at least one of four gravity sensors 11˜14 are arrangedat the heart valve auscultation sites 3 which are on the body surfaceand corresponding to the heart valves, including an aortic area 31, amitral area 32, a pulmonary area 33, and a tricuspid area 34. The aorticarea 31 is present from the left second intercostal space at the leftsternal border, over the sternum, to the right second to thirdintercostal space at the right sternal border. The mitral area 32 spansthe right fifth intercostal space at the right sternal border to theposterior axillary line. The pulmonary area 33 is around the left 2ndintercostal space at the left sternal border, up to the left firstintercostal space, a lower part of the clavicle, and then down to theleft third intercostal space at the left sternal border. The tricuspidarea 34 extend rightward from the right fourth to fifth intercostalspace at the right sternal border. Each gravity sensor 11˜14 contains anaccelerometer chip. The typical type of accelerometer chip can bepiezo-resistive, capacitive, piezoelectric and resonant while thepreferred one is produced and sold by the American company ADXL or theEuropean company STM. The accelerometer chip is used to measure thevibrations on the body surface and to acquire at least onemechanocardiography (MCG), which is also known as a seismocardiography(SCG).

The ECG sensing module 15 is disposed on a lead site on the skin areafor detecting the electrical activity of the heart on the skin area andproducing an electrocardiography. The optimal lead site includespositions for 3 limb leads-one right arm (RA), one left arm (LA), andone left leg (LL) and the lead is preferably attached proximally to thewrist and the ankle. The positions of the leads shown in FIG. 1 are onlyan embodiment of the present invention and are not limited to thesepositions.

The processor 16 is used for receiving at least one MCG and the ECGmentioned above, retrieving peaks or valleys of the P-wave, QRS complexand T-wave in the ECG, and comparing the peaks or valleys of the ECGwith the MCG within at least one time interval. Thus a plurality offeature points of the MCG are obtained within the time interval. Theoptimal processor 16 is a microcontroller unit.

The storage unit 17 used for receiving the feature points of the MCG andrecording both the ECG and at least one MCG from the processor 16 can bea Read-Only Memory (ROM), or a Random Access Memory (RAM). If thestorage unit 17 is the ROM, it is preferred to access and store signalinformation through an SD (secure digital) card by which the informationis delivered to a receiving device 5 directly. The receiving device 5can be a portable device, a computer, or a display.

The hardware of the present invention further includes a transmissionunit 18 that receives the MCG feature points, the ECG, and at least oneMCG from the processor 16, or the MCG feature points and at least oneMCG from the storage unit 17. The transmission unit 18 sends the abovesignal information to the receiving device 5 in a wired or wireless way.

Refer to FIG. 4 and FIG. 5, a flow chart showing steps and a graphshowing signal strength versus time of an embodiment according to thepresent invention are revealed. The horizontal axis of ECG1 and MCG1 istime (unit: sec) while the vertical axis of ECG1 is signal strength(unit: mV) and the vertical axis of MCG1 is also signal strength (unit:mG). A method of this implementation includes the following steps:

-   Step S1010: Arrange a gravity sensor at an aortic area on the body    surface that corresponds to heart valves to get a first MCG reading    (MCG 1) by the gravity sensor;-   Step S1020: Place an ECG sensing module on a lead attachment region    on the body surface to get an ECG reading;-   Step S1030: Retrieve a P-wave peak and an R-wave peak of the ECG 1    and correspond the P-wave peak and the R-wave peak to the MCG1 to    get a first corresponding point and a second corresponding point;    and-   Step S1040: Retrieve a peak with the maximum value between the first    corresponding point and the second corresponding point. The peak    with the maximum value is a transmitral atrial contraction maximal    flow feature point.

As shown in FIG. 1 and FIG. 3, in step S1010, the gravity sensor 11arranged at the aortic area 31 is used for receiving vibrations on thebody surface at the aortic area 31 caused by the heartbeat to get thefirst MCG reading (MCG1).

In step S1020, three limb leads of the ECG sensing module 15 are usedfor receiving electrophysiological signals of the heart over time to getthe ECG1. The processor 16 receives the MCG1 and the ECG1.

In step S1030, the processor 16 retrieves the P-wave peak and the R-wavepeak of the ECG 1 and then corresponds the P-wave peak and the R-wavepeak to the first MCG1 respectively to get a first corresponding pointO1 and a second corresponding point O2 on the MCG1. The horizontal axis(time) of the ECG1 and the horizontal axis (time) of the MCG1 aredependent on each other.

In step S1040, the processor 16 retrieves several peaks and valleys inturn within a time interval A1 between the first corresponding point O1and the second corresponding point O2 of the MCG1 so as to get the peakwith the maximum value. The peak with the maximum value that falls atthe position of 0.0225 second before the second corresponding point O2is a transmitral atrial contraction maximal flow feature point, MF_(A).

After step S1040, the processor 16 transmits the transmitral atrialcontraction maximal flow feature point (MF_(A)), the ECG1 and the MCG1to the storage unit 17 and the receiving device 5. Thus users can getthe information by a display 51 of the receiving device 5 in real time.Moreover, the storage unit 17 not only receives and records thetransmitral atrial contraction maximal flow feature point, MF_(A), theECG1 and the MCG1, but also transmits the above data to the receivingdevice 5 when users are not monitoring the data in real time. Thus userscan access the data history.

Refer to FIG. 6. A comparative diagram shows the signal strength versustime of a first observation. The horizontal axis of ECG1, ECG2, MCG1 andthe first Doppler Echocardiography (DG1) is time (unit: sec). Thevertical axis of the second ECG (ECG2) is signal strength (unit: mV) andthe vertical axis of MCG1 is also signal strength (unit: mG) while thevertical axis of the DG1 is the blood flow rate (unit: cm/s). In thisexperiment, a Doppler ultrasonic device (not shown in figure) is used todetect heartbeat-induced vibration on the body surface and get the DG1.An ultrasonic transducer of the Doppler ultrasonic device is mounted ona lateral wall of the left ventricle so as to identify the position ofthe MF_(A) and of the MCG1 at the same time. The ECG2 is measuredsimultaneously with the DG1. The ECG1 and the ECG2 are measured at thesame time so that the ECG2 and the ECG1 are consistent with each other.Moreover, the DG1, the MCG1, the ECG1 and the ECG2 are also measured atthe same time. The limb leads or precordial leads of the ECG2 are placedon the body surface. The six positions for the precordial leads on thechest are as follows: fourth intercostal space at right edge of sternum,fourth intercostal space at the left edge of sternum, midway between theprevious two positions, fifth intercostal space at the leftmidclavicular line, fifth intercostal space at the left anterioraxillary line, and fifth intercostal space at the left midaxillary line.

Refer to the DG1. There is a valley B1 with the minimum value showingmaximum atrial blood flow or blood pressure and considered to beidentical with the feature point MF_(A) by physicians. Accordance to thevalley B1 with the minimum value and the first time interval A1 betweenthe P-wave peak and R-wave peak of the MCG1, it is found that thetransmitral atrial contraction maximal flow feature point (MF_(A)) ofMCG1 and the valley B1 both fall within the first time interval A1. Thefeature point MF_(A) is with the maximum value among the peaks andvalleys within the first time interval A1 while the timing of thefeature point MF_(A) of the MCG1 and the timing of the valley B1 of theDG1 are nearly the same. Thus the feature point MF_(A) of the MCG1 andthe valley B1 of the DG1 are identical to each other.

Refer to FIG. 7 and FIG. 8, these figures are flow charts showing stepsand a second graph showing signal strength versus time of anotherexperiment, respectively. The unit of the horizontal axis and the unitof the vertical axis of ECG1 and MCG 1 in the second graph showingsignal strength versus time of this embodiment are the same, as arethose in the first graph showing signal strength versus time of theabove experiment. The hardware of this experiment is also the same asthe previous experiment. The difference between this experiment and theabove experiment is only in the retrieving time so that another featurepoint is identified. The method to identify this feature point includesthe following steps:

-   Step S1010: Place a gravity sensor on an aortic area on the body    surface that corresponds to heart valves to get a first MCG reading    (MCG 1) by the gravity sensor;-   Step S1020: Arrange an ECG sensing module at a lead attachment    region on the body surface to get an ECG;-   Step S1031: Retrieve a R-wave peak of the ECG1 and correspond the    R-wave peak to the MCG1 to get a second corresponding point; and-   Step S1041: Retrieve a valley with the minimum value and a peak    thereafter in turn within an interval of 0.06 seconds after the    second corresponding point O2. The peak is a lateral wall    contraction maximal velocity feature point (LCV).

Refer to FIG. 4. Step S1010 and step S1020 are the same as those of thefirst experiment.

Back to FIG. 1, in the step S1041, the processor 16 retrieves a seriesof peaks and valleys within a second time interval A2 between the secondcorresponding point O2 and a first time point T1 after the secondcorresponding point O2 of the MCG 1 to get the valley with minimum valueL1 and the following peak. The peak is preferred to be at the positionof 0.0575 seconds after the second corresponding point O2 and isrepresenting a lateral wall contraction maximal velocity feature point(LCV) while the optimal first time point T1 is 0.06 seconds.

After step S1041, the signals are recorded and stored as mentioned inthe above experiment.

Refer to FIG. 9. This figure is a comparative diagram of a secondexperiment. The unit of the horizontal axis and the unit of the verticalaxis of ECG1, ECG2, MCG1 and DG1 of this experiment is time with respectto those in the comparative diagram showing signal strength versus timeof the first embodiment shown in FIG. 6. Similar to the firstexperiment, this experiment also uses a Doppler ultrasonic device to getthe DG1 for identification of the position of the feature point LCV ofthe MCG1.

Refer to the DG1, a peak B2 with the maximum value that shows themaximum atrial blood flow or blood pressure is considered to beidentical with the feature point LCV by physicians. According to thepeak B2 with the maximum value and a plurality of peaks and valleys inthe second time interval A2 of the MCG1, it is found that both thefeature point LCV of the MCG1 and the peak B2 with the maximum value ofthe DG1 fall in the second time interval A2 after the valley L1 with theminimum value. Thus the feature point LCV of the MCG1 and the peak B2with the maximum value of the DG1 are identical to each other.

Refer to FIG. 10 and FIG. 11. A flow chart showing steps and a thirdgraph showing signal strength versus time of a further experiment,respectively, are disclosed. The unit of the horizontal axis and theunit of the vertical axis of ECG1 and MCG 1 in the third graph showingsignal strength versus time of this experiment are the same as those inthe first graph showing signal strength versus time of the firstexperiment. The hardware of this experiment is also the same with thefirst experiment. The difference between this experiment and the firstexperiment is only in the retrieving time so that a further featurepoint is identified. A method of this experiment includes followingsteps:

-   Step S1010: Set a gravity sensor on an aortic area on the body    surface that corresponds to heart valves to get a first MCG reading    (MCG 1) by the gravity sensor;-   Step S1020: Mount an ECG sensing module on a lead attachment region    on the body surface to get an ECG;-   Step S1031: Retrieve a R-wave peak of the ECG1 and correspond the    R-wave peak to the MCG1 to get a second corresponding point; and-   Step S1042: Retrieve a peak with the maximum value in an interval of    0.07-0.1 seconds after the second corresponding point O2. The peak    with the maximum value is a transaortic maximal flow feature point    (AF).

Refer to FIG. 4. Step S1010 and step S1020 are the same as those of thefirst experiment.

Back to FIG. 1, in step S1042, the processor 16 retrieves several peaksand valleys within a third time interval A3 between a second time pointT2 and a third time point T3 after the second corresponding point O2 ofthe MCG 1 to get a peak with the maximum value. The peak with themaximum value is preferred to be at the position of 0.09 seconds afterthe first corresponding point O1. The peak with the maximum value is atransaortic maximal flow feature point (AF) while the optimal secondtime point T2 is 0.07 seconds and the optimal third time point T3 is 0.1seconds.

After step S1042, the signals are recorded and stored as mentioned inthe above explanation.

Refer to FIG. 12. This figure is the third comparative diagram showingsignal strength versus time of a third experiment. The unit of thehorizontal axis and the unit of the vertical axis of ECG1, ECG2, MCG1and a second Doppler Echocardiography (DG2) are the same as those of thefirst comparative graph of the first experiment. In this experiment, aDoppler ultrasonic device is used to detect heartbeat-induced vibrationson the body surface and to get the DG2 reading while the DG2, MCG1, ECG1and ECG2 are measured at the same time. An ultrasonic transducer of theDoppler ultrasonic device is mounted on the left ventricle area andtoward the mitral valve so as to get the DG2 for synchronousidentification of the position of the feature point AF of the MCG1.

Refer to the DG2. There is a valley B3 with the minimum value showingmaximum atrial blood flow or blood pressure at the inner side of leftventricle, which is considered to be identical with the feature point AFby physicians according to the valley B3 with the minimum value andseveral peaks and valleys in the third time interval A3 of the MCG1. Inthis experiment, the feature point AF with the maximum value of MCG1 andthe valley B3 are falling into the third time interval A3 and arerepresenting the peak with the maximum value and the point with theminimum value among the peaks and valleys within the third time intervalA3 respectively. Thus the feature point AF of the first MCG1 and thevalley B3 with the minimum value of the DG2 are identical to each other.

Refer to FIG. 13 and FIG. 14. These figures represent a flow chartshowing steps and a fourth graph showing signal strength versus time ofa fourth embodiment, respectively. The unit of the horizontal axis andthe unit of the vertical axis of ECG1 and MCG 1 in the fourth graphshowing signal strength versus time of this experiment are the same asthose in the first graph showing signal strength versus time of thefirst experiment. The hardware of this experiment is also the same withthe above three experiments. The difference between this experiment andthe third experiment is only that the feature point AF is obtained in adifferent way. Similar to the second experiment, this experiment firstretrieves the feature point LCV and then finds out the feature point AFlocated after the feature point LCV. The method of this experimentincludes the following steps:

-   Step S1010: Arrange a gravity sensor at an aortic area on the body    surface that corresponds to the heart valves to get a first MCG    reading (MCG 1) by the gravity sensor;-   Step S1020: Place an ECG sensing module on a lead attachment region    on the body surface to get an ECG reading;-   Step S1031: Retrieve an R-wave peak of the ECG1 and correspond the    R-wave peak to the MCG1 to get a second corresponding point;-   Step S1041: Retrieve a valley with the minimum value and a peak    thereafter in turn within an interval of 0.06 seconds after the    second corresponding point O2. The peak is a lateral wall    contraction maximal velocity feature point (LCV); and-   Step S1043: Retrieve a valley and a peak after the LCV in turn; the    peak is a transaortic maximal flow feature point (AF).

Back to FIG. 7, step S1010 and step S1041 are the same as those of thesecond experiment.

In step S1043, the processor 16 retrieves a valley L2 and a peak afterthe LCV after the feature point LCV in turn while the peak is atransaortic maximal flow feature point (AF).

After step S1043, the signals are recorded and stored as mentioned inthe previous experiment.

The feature point AF of this experiment is at the same position of theMCG 1 as that of the above third experiment. Thereby this experiment canalso get the same identification result as the third experimentaccording to the DG 2.

Refer to FIG. 15 and FIG. 16. These figures are a flow chart showingsteps and a fifth graph showing signal strength versus time of a fifthexperiment, respectively. The unit of the horizontal axis and the unitof the vertical axis of ECG1 and MCG 1 in the fifth graph showing signalstrength versus time of this experiment are the same as those in thefirst graph showing signal strength versus time of the first experiment.The hardware of this experiment is also the same with the firstexperiment. The difference between this experiment and the firstexperiment is only in the retrieving time so that a further featurepoint is identified. A method of this experiment includes the followingsteps:

-   Step S1010: Mount a gravity sensor on an aortic area on the body    surface that corresponds to the heart valves to get a first MCG    reading (MCG 1) by the gravity sensor;-   Step S1020: Set an ECG sensing module on a lead attachment region on    the body surface to get an ECG;-   Step S1032: Retrieve an R-wave peak and a T-wave peak of the ECG1    that correspond to the R-wave peak and the T-wave peak to the MCG1    to get a second corresponding point and a third corresponding point;    and-   Step S1044: Retrieve a peak with the maximum value within an    interval between 0.1 seconds after the second corresponding point O2    and the third corresponding point O3; the peak with the maximum    value is a Transpulmonary maximal flow feature point (PF).

Refer to FIG. 7. Step S1010 and step S1020 are the same as those of thesecond experiment. The step S1032 is similar to step S1031 while onemore point (a T-wave peak of ECG1) is retrieved and corresponding to theMCG1 by the processor 16 MCG1 to get a third corresponding point O3.

In step S1044, the processor 16 retrieves several peaks and valleyswithin a fourth time interval A4 between the second time point T2 afterthe second corresponding point O2 and the third corresponding point O3of the MCG 1 to get a peak with the maximum value. The peak with themaximum value is preferred to be at the position of 0.07 seconds afterthe second corresponding point O2 and representing the transpulmonarymaximal flow feature point (PF) while the optimal second time point T2is 0.1 seconds.

After step S1044, the signals are recorded and stored as mentioned inthe previous experiment.

Refer to FIG. 17. This figure is a fourth comparative figure of a fifthexperiment. The unit of the horizontal axis and the unit of the verticalaxis of ECG1, ECG2, MCG1 and a third Doppler Echocardiography (DG3) arethe same as those of the first graph showing signal strength versus timeof the first experiment. In this experiment, a Doppler ultrasonic devicethe same with the one used in the first experiment is used to get theDG3 while the DG3, MCG1, ECG1 and ECG2 of this experiment are measuredat the same time. An ultrasonic transducer of the Doppler ultrasonicdevice is mounted on the right ventricle area and toward the pulmonaryvalve to receive vibrations caused by the heartbeat so as to get the DG3and identify the position of the feature point PF of the MCG1 at thesame time.

Refer to the DG3. There is a valley B4 with the minimum value showingmaximum blood flow or blood pressure of the right ventricle, which isconsidered to be identical with the feature point PF by physicians. Thisis in accordance to the valley B4 with the minimum value and severalpeaks and valleys in the fourth time interval A4 of the MCG1. Both thevalley B4 with the minimum value of the DG3 and the feature point PF ofthe MCG1 fall in the fourth time interval A4 while the feature point PFis the peak with the maximum value and the valley B4 with the minimumvalue within the fourth time interval A4. Thus the feature point PF ofthe MCG1 in this experiment is identical to the valley B4 with theminimum value of the DG3.

Refer to FIG. 18 and FIG. 19. These figures are a flow chart showingsteps and a sixth graph showing signal strength versus time of a sixthexperiment, respectively. The unit of the horizontal axis and the unitof the vertical axis of ECG1 and MCG 1 in the sixth graph showing signalstrength versus time of this experiment are the same as those in thefirst graph showing signal strength versus time of the first experiment.The hardware of this experiment is also the same with the above 5experiment. The difference between this experiment and the fifthexperiment is only in that the feature point PF is obtained in adifferent way. Similar to the second experiment, this experiment firstretrieves the feature point LCV and then finds out the feature point PFlocated after the feature point LCV. The method of this experimentincludes the following steps:

-   Step S1010: Arrange a gravity sensor at an aortic area on the body    surface that corresponds to the heart valves to get a first MCG    reading (MCG 1) by the gravity sensor;-   Step S1020: Place an ECG sensing module on a lead attachment region    on the body surface to get a ECG;-   Step S1032: Retrieve an R-wave peak and a T-wave peak of the ECG1    that corresponds to the R-wave peak and the T-wave peak to the MCG1    to get a second corresponding point and a third corresponding point;-   Step S1041: Retrieve a valley with the minimum value and a peak    thereafter in turn within an interval of 0.06 seconds after the    second corresponding point. The peak is a lateral wall contraction    maximal velocity feature point (LCV).-   Step S1045: Retrieve a peak with the maximum value within an    interval between the feature point LCV and the third corresponding    point. The peak with the maximum value is a transpulmonary maximal    flow feature point (PF).

Refer to FIG. 7 and FIG. 15. Steps S1010, S1020, and S1041 are the sameas those of the second experiment while step S1032 is the same as thatof the fifth experiment.

In step S1045, the processor 16 retrieves several peaks and valleyswithin a fifth time interval A5 between the feature point LCV and thethird corresponding point O3 of the MCG1 to get the peak with themaximum value. The peak with the maximum value represents the featurepoint PF.

After step S1045, the signals are recorded and stored as mentioned inthe previous experiment.

The feature point PF is at the same position of the MCG1 as the fifthexperiment. Thus the DC3 also have the same identification results asthose of the fifth experiment.

Refer to FIG. 20 and FIG. 21. These figures are a flow chart showingsteps and a seventh graph showing signal strength versus time of aseventh experiment, respectively. The unit of the horizontal axis andthe unit of the vertical axis of ECG1 and MCG 2 in the seventh graphshowing signal strength versus time of this experiment are the same asthose in the first signal-time graph of the first experiment. Thehardware of this experiment is almost the same with the firstexperiment, only different in the position of the gravity sensor 12(refer to FIG. 1) and the retrieving time is different to get anotherfeature point such as LCV of the second experiment. The method of thisexperiment includes the following steps:

-   Step S1011: Arrange a gravity sensor at the mitral area on the body    surface that corresponds to the heart valves to get a second MCG    reading (MCG 2) by the gravity sensor;-   Step S1020: Place an ECG sensing module on a lead attachment region    on the body surface to get a ECG;-   Step S1033: Retrieve an R-wave peak and a T-wave peak of the ECG1    and correspond the R-wave peak and the T-wave peak to the MCG2 to    get a fourth corresponding point and a fifth corresponding point;    and-   Step S1046: Retrieve a peak with the maximum value within an    interval between 0.04 seconds after the fourth corresponding point    and the fifth corresponding point. The peak with the maximum value    is a lateral wall contraction maximal velocity feature point (LCV).

As shown in FIG. 1 and FIG. 3, in step S1011, the gravity sensor 12placed on the mitral area 32 is used for receiving vibrations on thebody surface at the mitral area 32 caused by the heartbeat to get asecond MCG reading (MCG2).

Back to FIG. 4, step S1020 of this experiment is the same as that of thefirst experiment.

Refer to FIG. 15. Step S1033 of this experiment is similar to step S1032of the fifth experiment. The difference is only that the R-wave peak andthe T-wave peak correspond to the MCG2 to get a fourth correspondingpoint O4 and a fifth corresponding point O5 of the MCG2. The horizontalaxis(time) of the ECG1 and the horizontal axis(time) of the MCG2 aredependent.

In step S1046, the processor 16 retrieves several peaks and valleys in asixth time interval A6 between a fourth time point T4 after the fourthcorresponding point O4 and the fifth corresponding point O5 of the MCG 2to get a peak with the maximum value. The peak with the maximum value isa transpulmonary maximal flow feature point (PF), at the position of0.07 seconds after the fourth corresponding point O4. The optimal fourthtime point T4 is 0.04 seconds.

After step S1046, the signals are recorded and stored as mentioned inthe above experiment.

Refer to FIG. 22. This figure depicts a fifth comparative figure of aseventh experiment. The unit of the horizontal axis and the unit of thevertical axis of ECG1, ECG2, MCG2 and the first Doppler Echocardiography(DG1) are the same as those of the first graph showing signal strengthversus time of the first experiment. In this experiment, a Dopplerultrasonic device identical to the device used in the second experimentis used to detect heartbeat-induced vibrations on the body surface so asto identify the position of the feature point LCV of the MCG2 at thesame time. The DG1, MCG2, ECG1 and ECG2 of this experiment are measuredat the same time. According to the peak B2 with the maximum value andthe peaks and the valleys in the sixth time interval A6 of the MCG2,both the feature point LCV of the MCG2 and the peak B2 with the maximumvalue are falling into the sixth time interval A6 of the MCG2 and havingthe maximum value in the sixth time interval A6. Thus the feature pointLCV of the MCG2 and the peak B2 with the maximum value of the DG1 areidentical to each other.

Refer to FIG. 23 and FIG. 24. These figures depict a flow chart showingsteps and an eighth graph showing signal strength versus time of aneighth experiment, respectively. The unit of the horizontal axis and theunit of the vertical axis of ECG1 and MCG 3 in the eighth graph showingsignal strength versus time of this experiment are the same as those inthe first graph showing signal strength versus time of the firstexperiment. The hardware of this experiment is also the same as thefirst experiment. The difference between this experiment and the firstexperiment includes the position of the gravity sensor 13 and theretrieving time so that a further feature point is discovered. Themethod of this experiment includes the following steps:

-   Step S1012: Place a gravity sensor on the pulmonary area of the body    surface that corresponds to the heart valves to get a third MCG    reading (MCG3) by the gravity sensor;-   Step S1020: Place an ECG sensing module on a lead attachment region    on the body surface to get an ECG;-   Step S1034: Retrieve an R-wave peak of the ECG 1 that corresponds to    the R-wave peak to the MCG3 to get a sixth corresponding point.-   Step S1047: Retrieve a peak with the maximum value in an interval    between 0.07-0.1 seconds after the sixth corresponding point. The    peak with the maximum value is a septal wall contraction maximal    velocity feature point (SCV).

Refer to FIG. 1 and FIG. 3. In step S1012, the gravity sensor 13arranged at the pulmonary area 33 is used for receiving vibrations onthe body surface at the pulmonary area 33 caused by heartbeat to get athird MCG reading (MCG3).

Refer to FIG. 4. Step S1020 of this experiment is the same as that ofthe first experiment.

Refer to FIG. 7. Step S1034 of this experiment is similar to step S1031of the second experiment. The difference is that this experiment theR-wave peak of the ECG1 corresponds to the MCG3 to get a sixthcorresponding point O6 of the MCG3. The horizontal axis(time) of theECG1 and the horizontal axis(time) of the MCG3 are dependent.

In step S1047, the processor 16 retrieves several peaks and valleyswithin a seventh time interval A7 between a second time point T2 and athird time point T3 after the sixth corresponding point O6 of the MCG 3to get a peak with the maximum value. The peak with the maximum peakvalue is preferred to be at the position of 0.082 seconds after thesixth corresponding point O6 and is representing a septal wallcontraction maximal velocity feature point (SCV).

After step S1047, the signals are recorded and stored as mentionedpreviously.

Refer to FIG. 25. This figure is the sixth comparative figure of aeighth experiment. The unit of the horizontal axis and the unit of thevertical axis of ECG1, ECG2, MCG1 and a fourth Doppler Echocardiography(DG4) are the same as those of the first graph showing signal strengthversus time of the first experiment. In this experiment, a Dopplerultrasonic device similar to that used in the third experiment is usedand the ultrasonic transducer of the Doppler ultrasonic device ismounted at the same position while the DG4, MCG3, ECG1 and ECG2 of thisexperiment are also measured at the same time. The difference is thatthe ultrasonic transducer is placed toward the septal wall to get theDG4 and identify the position of the feature point SCV of the MCG3 atthe same time.

Refer to the DG4. There is a peak B5 with the maximum value that showsthe maximal velocity of the septal wall, which considered to beidentical with the feature point LCV by physicians. This is inaccordance to the peak B5 with the maximum value and a seventh timeinterval A7 of the MCG3. Both the feature point SCV of the MCG3 and thepeak B5 with the maximum value of the DG4 fall in the seventh timeinterval A7 and are with the maximum value in the seventh time intervalA7. Thus the feature point SCV of the MCG3 and the peak B5 with themaximum value of the DG4 are identical to each other.

Refer to FIG. 26 and FIG. 27. These figures are a flow chart showingsteps and a ninth graph showing signal strength versus time of a ninthexperiment, respectively. The unit of the horizontal axis and the unitof the vertical axis of ECG1, MCG 1 and MCG3 in the ninth graph showingsignal strength versus time of this experiment are the same as those inthe first graph showing signal strength versus time of the firstexperiment. The hardware of this experiment is the same as the eighthexperiment and only the method to obtain the feature point SCV differs.As in the second experiment, this experiment first retrieves the featurepoint LCV, then finds out the feature point

-   SCV after the feature point LCV. The method of this experiment    includes the following steps:-   Step S1013: Place several gravity sensors on the aortic area and the    pulmonary area on the body surface that correspond to the heart    valves so as to get a first-   MCG reading (MCG1) and a third MCG reading (MCG3) via the gravity    sensors;-   Step S1020: Place an ECG sensing module on a lead attachment region    on the body surface to get an ECG;-   Step S1031: Retrieve an R-wave peak of the ECG1 and correspond the    R-wave peak to the MCG1 to get a second corresponding point;-   Step S1041: Retrieve a valley with the minimum value and a peak    thereafter in turn within an interval of 0.06 seconds after the    second corresponding point O2. The peak is a lateral wall    contraction maximal velocity feature point (LCV);-   Step S1050: Correspond the feature point LCV to the MCG3 to get a    seventh corresponding point; and-   Step S1060: Retrieve a peak after the seventh corresponding point.    This peak is a septal wall contraction maximal velocity feature    point (SCV).

Refer to FIG. 7 and FIG. 23. Step S1013 of this experiment is the sameas step S1010 of the second experiment combined with step S1012 of theeighth experiment. Step S1020, step S1031, and step S1041 of thisexperiment are the same as those of the second experiment.

In step S1050, the processor 16 corresponds the feature point LCV of theMCG 1 to the MCG3 to get the seventh corresponding point O7. The MCG1and the MCG3 are time dependent.

In step S1060, the processor 16 retrieves a valley L3 and a peak afterthe seventh corresponding point O7 of the MCG3 in turn that representsthe feature point SCV.

After step S1060, the signals are recorded and stored as mentioned inthe previous experiment.

The SCV of this experiment is at the same position of the MCG3 as theeighth experiment. Thus the DGS also displays similar results as thoseof the eighth experiment.

Refer to FIG. 28 and FIG. 29. These figures depict a flow chart showingsteps and a tenth graph showing signal strength versus time of a tenthexperiment, respectively. The unit of the horizontal axis and the unitof the vertical axis of ECG1 and MCG 4 in the tenth graph showing signalstrength versus time of this experiment are the same as those in thefirst graph showing signal strength versus time of the first experiment.The hardware of this experiment is also the same as the firstexperiment. The difference between this experiment and other experimentsis that this experiment obtains a feature point similar to the featurepoint LCV of the second experiment (in FIG. 8). The method of thisexperiment includes the following steps:

-   Step S1014: Place a gravity sensor on the tricuspid area on the body    surface that corresponds to the heart valves to get a fourth MCG    (MCG4) by the gravity sensor;-   Step S1020: Place an ECG sensing module on a lead attachment region    on the body surface to get a ECG;-   Step S1035: Retrieve an R-wave peak and a T-wave peak of the ECG1    that correspond to the R-wave peak and the T-wave peak to the MCG4    to get an eighth corresponding point and a ninth corresponding    point.-   Step S1048: Retrieve a peak with the maximum value between the    eighth corresponding point and the ninth corresponding point. The    peak with the maximum value is a lateral wall contraction maximal    velocity feature point (LCV).

Refer to FIG. 1 and FIG. 3. In step S1014, the gravity sensor 14arranged at the tricuspid area 34 is used for receiving vibrations onthe body surface at the tricuspid area 34 caused by the heartbeat to geta fourth MCG reading (MCG4). As in step S1020, this is the same theprocedure is the same as that of the first experiment.

In step S1035, the processor 16 retrieves the R-wave peak and the T-wavepeak of the ECG1 and correspond the R-wave peak and the T-wave peak tothe MCG4 to get an eighth corresponding point O8 and a ninthcorresponding point O9 of the MCG4. The horizontal axis (time) of theECG1 and the horizontal axis (time) of the MCG4 are dependent.

In step S1048, the processor 16 retrieves several peaks and valleyswithin an eighth time interval A8 between the eighth corresponding pointO8 and the ninth corresponding point O9 to get a peak with the maximumvalue. The peak with the maximum value that falls at the position 0.05seconds after the eighth corresponding point O8 is the feature pointLCV.

After step S1048, the signals are recorded and stored as mentioned inthe previous experiment.

Refer to FIG. 30. This figure depicts a comparative figure of the tenthexperiment of the present invention. As shown in the figure, thehorizontal axis and the vertical axis of the ECG1, the ECG2, the MCG4and the DG1 in this figure are the same as those of the firstcomparative figure of the first experiment. Similar to the first and thesecond experiment, a Doppler ultrasonic device is used to detectheartbeat-induced vibrations on the body surface and obtain the DG1 foridentification of the position of the feature point LCV of the MCG1 atthe same time.

Refer to the DG1. There is a peak B2 with the maximum value showingmaximum contraction velocity of the lateral wall at the left ventricleand being considered to be identical with the feature point LCV byphysicians. This is in accordance to the peak B2 with the maximum valueand several peaks and valleys in the eighth time interval A8 of theMCG4. Both the feature point LCV of the MCG4 and the peak B2 with themaximum value of the DG1 fall in the eighth time interval A8 while theB2 and the LCV are peaks with the maximum value within the eighth timeinterval A8. Thus the feature point LCV of the MCG4 and the peak B2 withthe maximum value of the DG1 are identical to each other. In summary,the above experiments use at least one gravity sensor 11-14 to get thetransmitral atrial contraction maximal flow feature point (MF_(A)), thelateral wall contraction maximal velocity feature point (LCV), thetransaortic maximal flow feature point (AF), the trans-pulmonary maximalflow feature point (PF) and the septal wall contraction maximal velocityfeature point (SCV). The MCG has the feature of multi-dimensionalobservation provided by at least one gravity sensor. Moreover, thefeature point identification method for mechanocardiography of thepresent invention retrieves the feature point LCV and uses the LCV asthe baseline, and then the feature point AF, the feature point PF andthe feature point SCV are further retrieved. The gravity sensors 11-14used in the present invention are lightweight and portable. Comparedwith ultrasonic devices used in medical institutes, the convenience inmeasurement is improved. Furthermore, several Doppler echocardiographsDG1˜DG4 are obtained by using the Doppler ultrasonic device to detectheartbeat-induced vibrations on the body surface corresponding to heartvalves. The results show that the gravity sensors 11˜14 get the featurepoints (MF_(A), LCV, AF, PF, and SCV) of the MCG corresponding to thesame time sequences of the Doppler echocardiography. The above resultsare all assessed and confirmed by physicians.

In summary, the feature point identification method formechanocardiography of the present invention uses gravity sensorsdisposed on heart valve auscultation sites including an aortic area, amitral area, a pulmonary area and a tricuspid area to get featurepoints. The gravity sensors measure the vibrations on the body surfaceto get a first MCG, a second MCG, a third MCG, and a fourth MCG, whichare compared with P-wave peak, R-wave peak and T-wave peak of at leastone ECG measured by ECG sensing module to get corresponding points. Thenseveral peaks and valleys within a certain time interval are retrievedto get readings related to heart valves, myocardial contraction andcardiac blood flow, including the transmitral atrial contraction maximalflow feature point (MF_(A)), the lateral wall contraction maximalvelocity feature point (LCV), the transaortic maximal flow feature point(AF), the trans-pulmonary maximal flow feature point (PF) and the septalwall contraction maximal velocity feature point (SCV). In addition, atleast one MCG is compared with the Doppler Echocardiography andphysicians have checked and identified the above features related toheart valves, myocardial contraction and cardiac blood flow asconsistent with the results of the Doppler Echocardiography. Thereforethe present invention provides physicians with the signal strength ortime parameter related to the feature points of the MCG for assessmentof heart valvular diseases and physicians can combine the feature pointsof the MCG with data obtained by medical equipment so as to improve theaccuracy of disease assessment.

Additional advantages and modifications will readily occur to thosepracticing this field and related fields. Therefore, the invention inits broader aspects is not limited to the specific details, andrepresentative devices shown and described herein. Accordingly, variousmodifications may be made without departing from the spirit or scope ofthe general inventive concept as defined by the appended claims andtheir equivalents.

What is claimed is:
 1. A feature point identification method formechanocardiography (MCG) applied to get a transmitral atrialcontraction maximal flow feature point (MFA) comprising the steps of:arranging a gravity sensor at an aortic area on a body surfacecorresponding to a patient's heart valves to get a first MCG reading bythe gravity sensor; placing an electrocardiography (ECG) sensing moduleon a limb lead attachment region on the body surface to get an ECG;determining a P-wave peak and an R-wave peak of the ECG andcorresponding the P-wave peak and the R-wave peak to the first MCGreading to get a first corresponding point and a second correspondingpoint; and determining a peak with the maximum value between the firstcorresponding point and the second corresponding point; wherein the peakwith the maximum value is the transmitral atrial contraction maximalflow feature point (MFA); wherein a processor is used to receive atleast one MCG obtained by said gravity sensor and said ECG obtained bythe ECG sensing module, said processor determines peaks or valleys ofR-waves in said ECG and comparing the peaks or valleys of said ECG withat least one said MCG to get at least one said corresponding point ofsaid MCG.
 2. The method as claimed in claim 1, wherein the aortic areais present from the left second intercostal space at the left sternalborder, over the sternum rightward, to the right second to thirdintercostal space at the right sternal border.
 3. The method as claimedin claim 1, wherein the limb lead attachment region includes one rightarm (RA), one left arm (LA), and one left leg (LL).
 4. A feature pointidentification method for mechanocardiography (MCG) applied to get alateral wall contraction maximal velocity feature point (LCV) comprisingthe steps of: disposing a gravity sensor at an aortic area on a bodysurface corresponding to a patient's heart valves to get a first MCGreading by the gravity sensor; arranging an electrocardiography (ECG)sensing module at a limb lead attachment region on the body surface toget an ECG; determining an R-wave peak of the ECG and corresponding theR-wave peak to the first MCG reading to get a second correspondingpoint; and retrieving a valley with the minimum value and a peakthereafter in turn within an interval of 0.06 seconds after the secondcorresponding point; wherein the peak is the lateral wall contractionmaximal velocity feature point (LCV).
 5. The method as claimed in claim4, wherein the aortic area is present from the left second intercostalspace at the left sternal border, over the sternum rightward, to theright second to third intercostal space at the right sternal border. 6.The method as claimed in claim 4, wherein the limb lead attachmentregion includes one right arm (RA), one left arm (LA), and one left leg(LL).
 7. A feature point identification method for mechanocardiography(MCG) applied to get a transaortic maximal flow feature point (AF)comprising the steps of: arranging a gravity sensor at an aortic area ona body surface corresponding to a patient's heart valves to get a firstMCG reading by the gravity sensor; setting an electrocardiography (ECG)sensing module at a limb lead attachment region on the body surface toget an ECG; determining an R-wave peak of the ECG and corresponding theR-wave peak to the first MCG reading to get a second correspondingpoint; and determining a peak with the maximum value in an interval of0.07-0.1 seconds after the second corresponding point; wherein the peakwith the maximum value is the transaortic maximal flow feature point(AF).
 8. The method as claimed in claim 7, wherein the aortic area ispresent from the left second intercostal space at the left sternalborder, over the sternum rightward, to the right second to thirdintercostal space at the right sternal border.
 9. The method as claimedin claim 7, wherein the limb lead attachment region includes one rightarm (RA), one left arm (LA), and one left leg (LL).
 10. A feature pointidentification method for mechanocardiography (MCG) applied to get atranspulmonary maximal flow feature point (PF) comprising the steps of:setting a gravity sensor on an aortic area on a body surfacecorresponding to a patient's heart valves to get a first MCG reading bythe gravity sensor; placing an electrocardiography (ECG) sensing moduleat a limb lead attachment region on the body surface to get an ECG;determining an R-wave peak and a T-wave peak of the ECG andcorresponding the R-wave peak and the T-wave peak of the first MCGreading, respectively, to get a second corresponding point and a thirdcorresponding point; and determining a peak with the maximum valuewithin an interval from 0.1 seconds after the second corresponding pointand the third corresponding point; wherein the peak with the maximumvalue is the transpulmonary maximal flow feature point (PF).
 11. Themethod as claimed in claim 10, wherein the aortic area is present fromthe left second intercostal space at the left sternal border, over thesternum rightward, to the right second to third intercostal space at theright sternal border.
 12. The method as claimed in claim 10, wherein thelimb lead attachment region includes one right arm (RA), one left arm(LA), and one left leg (LL).
 13. A feature point identification methodfor mechanocardiography (MCG) applied to get a transpulmonary maximalflow feature point (PF) comprising the steps of: arranging a gravitysensor on an aortic area on a body surface corresponding to a patient'sheart valves to get a first MCG reading by the gravity sensor; placingan electrocardiography (ECG) sensing module at a limb lead attachmentregion on the body surface to get an ECG; determining an R-wave peak anda T-wave peak of the ECG and corresponding the R-wave peak and theT-wave peak to the first MCG reading, respectively, to get a secondcorresponding point and a third corresponding point; determining avalley with the minimum value and a peak thereafter in turn within aninterval of 0.06 seconds after the second corresponding point; whereinthe peak is a lateral wall contraction maximal velocity feature point(LCV); and determining a peak with the maximum value within an intervalbetween the feature point LCV and the third corresponding point; whereinthe peak with the maximum value is the transpulmonary maximal flowfeature point (PF).
 14. The method as claimed in claim 13, wherein theaortic area is present from the left second intercostal space at theleft sternal border, over the sternum rightward, to the right second tothird intercostal space at the right sternal border.
 15. The method asclaimed in claim 13, wherein the limb lead attachment region includesone right arm (RA), one left arm (LA), and one left leg (LL).
 16. Afeature point identification method for mechanocardiography (MCG)applied to get a septal wall contraction maximal velocity feature point(SCV) comprising the steps of: placing several gravity sensors on anaortic area and a pulmonary area on a body surface corresponding to apatient's heart valves to get a first MCG reading and a third MCGreading by the gravity sensors respectively; arranging anelectrocardiography (ECG) sensing module at a limb lead attachmentregion on the body surface to get an ECG; determining an R-wave peak ofthe ECG and corresponding the R-wave peak to the first MCG reading toget a second corresponding point; and determining a valley with theminimum value and a peak thereafter in turn within an interval of 0.06seconds after the second corresponding point; wherein the peak is alateral wall contraction maximal velocity feature point (LCV);corresponding the feature point LCV to the third MCG to get a seventhcorresponding point; and determining a peak after the seventhcorresponding point; wherein the peak is the septal wall contractionmaximal velocity feature point (SCV).
 17. The method as claimed in claim16, wherein the aortic area is present from the left second intercostalspace at the left sternal border, over the sternum rightward, to theright second to third intercostal space at the right sternal border; thepulmonary area is around the left second intercostal space at the leftsternal border, up to the left first intercostal space, a lower part ofthe clavicle, and then down to the left third intercostal space at theleft sternal border.
 18. The method as claimed in claim 16, wherein thelimb lead attachment region includes one right arm (RA), one left arm(LA), and one left leg (LL).
 19. A feature point identification methodfor mechanocardiography (MCG) applied to get a lateral wall contractionmaximal velocity feature point (LCV) comprising the steps of: placing agravity sensor on a tricuspid area on a body surface corresponding to apatient's heart valves to get an MCG reading by the gravity sensor;setting an electrocardiography (ECG) sensing module on a limb leadattachment region on the body surface to get an ECG; determining anR-wave peak and a T-wave peak of the ECG and corresponding the R-wavepeak and the T-wave peak to the fourth MCG reading, respectively, to getan eighth corresponding point and a ninth corresponding point; anddetermining a peak with the maximum value between the eighthcorresponding point and the ninth corresponding point; wherein the peakwith the maximum value is the lateral wall contraction maximal velocityfeature point (LCV).
 20. The method as claimed in claim 19, wherein thetricuspid area is extended rightward from the left fourth to fifthintercostal space at the right sternal border.
 21. The method as claimedin claim 19, wherein the limb lead attachment region includes one rightarm (RA), one left arm (LA), and one left leg (LL).